Hidden Markov Random Field and Gaussian Mixture Model Based Hidden Markov Random Field for Contour Labelling of Exudates in Diabetic Retinopathy—A Comparative Study
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-00665-5_123
Reference21 articles.
1. Ram P, Swapna TR (2018) Profiling of hard exudates and microaneurysms to evaluate the progress of diabetic retinopathy. Int J Pure Appl Math 118(Special Issue 8):127–131
2. Ahmad A et al (2014) Image processing and classification in diabetic retinopathy: a review. In: 2014 5th European workshop on visual information processing (EUVIP). IEEE
3. Hussain F, Nandi Jaafar AK, Al-Nuaimy W (2010) Automated detection of exudates in retinal images using a splitand-merge algorithm. In: European signal processing conference, EUSIPCO
4. Choudhury S et al (2016) Fuzzy C means based feature extraction and classification of diabetic retinopathy using support vector machines. In: 2016 International conference on communication and signal processing (ICCSP). IEEE
5. Harini R, Sheela N (2016) Feature extraction and classification of retinal images for automated detection of diabetic retinopathy. In: 2016 Second international conference on cognitive computing and information processing (CCIP). IEEE
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